Senior Data Integration Engineer

Job Summary

We are seeking a highly experienced and strategic Senior Data Integration Engineer to architect, build, and manage the data pipelines that power our customer intelligence ecosystem. In this critical role, you will be the subject matter expert responsible for designing and implementing robust integrations between our core platforms: Salesforce Data Cloud, Databricks, and MuleSoft.

You will be responsible for creating a seamless flow of data, enabling advanced analytics, and empowering our business to activate real-time customer insights. The ideal candidate is a hands-on expert who can translate complex business requirements into scalable, secure, and high-performance technical solutions.

Key Responsibilities

• Architect Integration Solutions:
  Lead the design and architecture of data integration patterns and end-to-end data flows between source systems, MuleSoft, Databricks, and Salesforce Data Cloud.
• Develop MuleSoft APIs:
  Design, develop, and deploy reusable, API-led integration solutions using MuleSoft's Any point Platform to ingest data into the ecosystem and to syndicate data to downstream systems.
• Build Advanced Data Pipelines in Databricks:
  Implement complex data transformation, cleansing, and enrichment pipelines using PySpark and SQL within the Databricks Lakehouse Platform. Prepare and model data for ingestion into Salesforce Data Cloud and for advanced analytics use cases.
• Master Salesforce Data Cloud:
  Configure and manage Salesforce Data Cloud, including setting up data streams, performing data mapping and harmonization, defining identity resolution rules, and creating insightful calculated metrics.
• Enable Data Activation:
  Collaborate with marketing, sales, and service teams to build and activate complex audience segments from Salesforce Data Cloud for use in personalization and campaign execution.
• Ensure Governance and Performance:
  Implement data quality checks, error handling, and performance monitoring across all platforms. Ensure solutions adhere to data governance policies, security standards, and privacy regulations.
• Mentorship and Best Practices:
  Act as a senior technical resource for the team, establishing best practices for integration and data engineering. Provide guidance and mentorship to junior team members.
• Stakeholder Collaboration:
  Work closely with business analysts, data scientists, and platform owners to gather requirements and deliver solutions that provide tangible business value.

Required Skills & Experience

• 6+ years of professional experience
  in a data engineering, integration development, or data architecture role.
• Proven hands-on experience with MuleSoft:
  Demonstrable expertise in designing, building, and managing APIs using the Any point Platform (API-led connectivity, Data Weave, connectors).
• Strong proficiency in Databricks:
  Hands-on experience developing data pipelines using
  PySpark
  , SQL, Delta Lake, and job orchestration.
• Demonstrable experience with Salesforce Data Cloud:
  In-depth knowledge of its data model, ingestion methods (Connectors, Ingestion API), identity resolution, segmentation, and activation capabilities.
• Expert SQL & Python Skills:
  Ability to write complex, efficient SQL queries and Python code for data manipulation and automation.
• Solid understanding of data modeling principles
  and experience designing and working with ETL/ELT processes.
• Experience working with major cloud platforms (
  AWS, Azure, or GCP
  ).

Preferred Qualifications

Certifications:

• Salesforce Data Cloud Consultant
• MuleSoft Certified Developer / Architect
• Databricks Certified Data Engineer Professional
• Experience with other Salesforce clouds (e.g., Marketing Cloud, Sales Cloud).
• Knowledge of CI/CD and DevOps practices in a data context.
• Familiarity with streaming data technologies (e.g., Kafka).